Survey of Fraud Detection Techniques for Credit Card Transactions

Ola Imran Obaid; Ali Yakoob Al-Sultan

doi:10.29196/jubpas.v32i2.5283

Article Details

Survey of Fraud Detection Techniques for Credit Card Transactions

Authors:

Ola Imran Obaid | Ali Yakoob Al-Sultan

Publisher:

University of Babylon

Journal:

JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.32 Issue 2, pp.226-244

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001383220

pISSN:

2312-8135

DOI:

10.29196/jubpas.v32i2.5283

Keywords:

Abstract:

 With the rapid advancement of Internet technology in recent years, online financial transactions have become increasingly popular for purchasing a wide range of goods and services over the Internet, owing to their numerous advantages. The widespread adoption of credit cards has thus heightened the potential for abuse. Present a significant menace to users as a result of pervasive fraudulent operations. Credit card fraud has become an essential concern in today's digital era, posing substantial financial losses and security risks for financial institutions and consumers. In response to this growing challenge, researchers and industry experts have continuously developed and refined fraud detection techniques to safeguard against fraudulent activities. This survey paper aims to provide a comprehensive overview of the latest advances in fraud detection techniques for credit card transactions. Explore various methodologies, data sources, and machine learning algorithms used in fraud detection systems. Additionally, they discuss the challenges these systems face.

Article Details

Survey of Fraud Detection Techniques for Credit Card Transactions

Authors:

Ola Imran Obaid | Ali Yakoob Al-Sultan

Publisher:

University of Babylon

Journal:

JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.32 Issue 2, pp.226-244

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001383220

pISSN:

2312-8135

DOI:

10.29196/jubpas.v32i2.5283

Fraud Detection

Anomaly Detection

Credit Cards

deep learning

long short-term memory

Issues

Article Details

Survey of Fraud Detection Techniques for Credit Card Transactions

Authors: Ola Imran Obaid | Ali Yakoob Al-Sultan

Publisher: University of Babylon

Journal: JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.32 Issue 2, pp.226-244

Document Type: Article

Publication Date: 1/2024

Document Language: English

Document ID (Org No.): 2001383220

pISSN: 2312-8135

DOI: 10.29196/jubpas.v32i2.5283

Fraud Detection

Anomaly Detection

Credit Cards

deep learning

long short-term memory

Issues

Authors:

Ola Imran Obaid | Ali Yakoob Al-Sultan

Publisher:

University of Babylon

Journal:

JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences Vol.32 Issue 2, pp.226-244

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001383220

pISSN:

2312-8135

DOI:

10.29196/jubpas.v32i2.5283